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24 results for “nlmixr2”
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One of the things I often get asked is if you can use #nlmixr2 in submissions. We were invited to meet with some of the FDA reviewers, and they confirmed they have received submissions in nlmixr2 and no issues were raised about its use
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New features in #nlmixr2 4.0, a #rstats package include a vere-style loading, importing models from older versions of nlmixr2 and Rstudio bug fixes. See https://blog.nlmixr2.org/blog/2025-08-29-nlmixr2-verse/
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nlmixr2 and rxode2 3.0 is out. It is a major release since there are some backward-incompatible changes. #nlmixr2 #rxode2 #rstats
https://blog.nlmixr2.org/blog/2024-09-18-nlmixr2-3.0.0-release/
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We have a new nlmixr2 blog entry courtesy of Hitesh Mistry and Nicola Melillo (@NicolaMelillo) detailing how to upscale nlmixr2 using AWS. This is helpful for long running SAEM models. In the future it may be even more interesting with other methods parallelized. (#nlmixr2 #rstats)
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A new version of #nlmixr2 was released on CRAN today. I will talk about a few features in the future:
- More flexible mu referencing
- User defined functions can now be used with nlmixr2 and rxode2
- Event handling changes
- Many new estimation methods for population only fitting
I am very grateful for both the nlmixr2 team and the nlmixr2 users who have helped me get to this point in nlmixr2's development.See the blog for more details about the release.
https://blog.nlmixr2.org/blog/2024-01-09-nlmixr2-2.1.0-release/
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Our colleagues at LAP&P are hosting a target-mediated drug disposition #TMDD course using #nlmixr2 at #PAGE2023 in A Coruña, Spain!
This is your chance to see nlmixr2 put through its paces in real-world #pharmacometrics by a world-class consulting team.
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That's what I was thinking. I think #nlmixr2 would fit right in there. Do you know folks at Roche? We should approach them.
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I would like to mention a new release of #nlmixr2. I haven't posted about it but I would like to mention my favorite new features:
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Hi everyone! This is the official home of #nlmixr2 on Mastodon. We are a constellation of #rstats packages aimed at supporting easy and robust nonlinear mixed-effects models in R. We are free and #OpenSource and will be forever.
Stay tuned for announcements of blog postings, chat, trivia, and whatever you all want to talk about!
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Modeling tools in our area are largely closed-source and massively expensive, and are a gigantic entry barrier for new people, especially in low and middle-income countries (and borderline unaffordable even for CROs like mine). #nlmixr2 is intended to be a solution to this problem. I also maintain the #pmxTools package, which provides a handy set of general #PMx functions.
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Latest from the new R Consortium nlmixr2 Working Group:
nlmixr2—an R-based, open-source nonlinear mixed-effects modeling package that can compete with commercial pharmacometrics tools and support regulatory submissions—now supports inter-occasion variability (IOV).
Read the full details in their newest blog post:
https://r-consortium.org/posts/from-nlmixr2-working-group-nlmixr2-inter-occasion-variability -
Want a single language for a few pharmcometric applications? How about giving #babelmixr2, an extension of #nlmixr2 a try?
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I'm on fosstodon.org because I do a lot of #rstats development, most notably as a member of the #nlmixr2 development team. nlmixr2 is a set of packages - let's call it the #mixrverse - for R that provides an #OpenSource alternative for nonlinear mixed-effects (#NLME) model development, which are the core of most #Pharmacometrics workflows (amongst others).
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R Consortium working groups are a practical on-ramp into the R community: open collaboration, technical contribution, and domain-specific work - often without needing to be from an R Consortium member company.
The nlmixr2 working group has a new post on an invited seminar with FDA quantitative clinical pharmacology reviewers, covering open source tools, regulatory review, reproducibility, model interchange, and reviewer-friendly workflows.
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R Consortium working groups are a practical on-ramp into the R community: open collaboration, technical contribution, and domain-specific work - often without needing to be from an R Consortium member company.
The nlmixr2 working group has a new post on an invited seminar with FDA quantitative clinical pharmacology reviewers, covering open source tools, regulatory review, reproducibility, model interchange, and reviewer-friendly workflows.
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R Consortium working groups are a practical on-ramp into the R community: open collaboration, technical contribution, and domain-specific work - often without needing to be from an R Consortium member company.
The nlmixr2 working group has a new post on an invited seminar with FDA quantitative clinical pharmacology reviewers, covering open source tools, regulatory review, reproducibility, model interchange, and reviewer-friendly workflows.
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R Consortium working groups are a practical on-ramp into the R community: open collaboration, technical contribution, and domain-specific work - often without needing to be from an R Consortium member company.
The nlmixr2 working group has a new post on an invited seminar with FDA quantitative clinical pharmacology reviewers, covering open source tools, regulatory review, reproducibility, model interchange, and reviewer-friendly workflows.
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R Consortium working groups are a practical on-ramp into the R community: open collaboration, technical contribution, and domain-specific work - often without needing to be from an R Consortium member company.
The nlmixr2 working group has a new post on an invited seminar with FDA quantitative clinical pharmacology reviewers, covering open source tools, regulatory review, reproducibility, model interchange, and reviewer-friendly workflows.
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Well, it's nice to know AI has limitations. 😃
(This code is largely nonsense.)
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#introduction time! I’m Justin Wilkins, a #pharmacometrics consultant living in Germany. I work for a small CRO called Occams and I post occasionally about #healthscience, modeling and simulation, #rstats and the current wretched state of British politics. I’m a co-developer of the nonlinear mixed-effects model fitting package #nlmixr2 in R, as well as the #pmxTools package.
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Hello to all our new followers! We’re delighted that so many are interested in our modest little project.
Our mission is to make #Pharmacometrics accessible to everyone, regardless of where they live and how much money their institutions have. The gold standard tools in our field typically cost >100K US$ per year for a reasonable license. We cost US$ 0.
Help us change the world! (Well, our tiny corner of it in any case)